code: def export_do_not_keepdims() -> None:
      shape = [3, 2, 2]
      axes = np.array([1], dtype=np.int64)
      keepdims = 0
      node = onnx.helper.make_node(
          "ReduceLogSumExp",
          inputs=["data", "axes"],
          outputs=["reduced"],
          keepdims=keepdims,
      )
  
      data = np.array(
          [[[5, 1], [20, 2]], [[30, 1], [40, 2]], [[55, 1], [60, 2]]],
          dtype=np.double,
      )
      reduced = np.log(
          np.sum(np.exp(data), axis=tuple(axes), keepdims=keepdims == 1)
      )
      # print(reduced)
      # [[20., 2.31326175]
      # [40.00004578, 2.31326175]
      # [60.00671387, 2.31326175]]
  
      expect(
          node,
          inputs=[data, axes],
          outputs=[reduced],
          name="test_reduce_log_sum_exp_do_not_keepdims_example",
      )
  
      np.random.seed(0)
      data = np.random.uniform(-10, 10, shape).astype(np.double)
      reduced = np.log(
          np.sum(np.exp(data), axis=tuple(axes), keepdims=keepdims == 1)
      )
  
      expect(
          node,
          inputs=[data, axes],
          outputs=[reduced],
          name="test_reduce_log_sum_exp_do_not_keepdims_random",
      )
  
file_path: onnx/onnx/backend/test/case/node/reduce_log_sum_exp.py
imports: import numpy
  import onnx
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
label_desc: Use image node_id 1 for calling the ReduceLogSumExp obj's underlying member method code with example usage: obj.export_do_not_keepdims() without return types